A Review of District Heating Systems: Modeling and Optimization

The ever-increasing demand for heating in different sectors, along with more preventative regulations on greenhouse emissions, has forced different countries to seek new alternative to heat buildings such as District Heating System (DHS). Although the traces of district heating systems can be observed over the centuries, it was not widely implemented until last two decades when the DHS become a method to design more green and energy efficient way for heating buildings. This paper tries to review the state of the art in modeling different components of the district heating systems and state the advantages as well as limitation of each method. Also, different methods used for the optimization of the DHSs have been reviewed.

[1]  Shem Heiple,et al.  Using building energy simulation and geospatial modeling techniques to determine high resolution building sector energy consumption profiles , 2008 .

[2]  Zbigniew Michalewicz,et al.  Simulation and Optimization , 2014 .

[3]  Jan Carmeliet,et al.  Predicting energy consumption of a neighbourhood using building performance simulations , 2014 .

[4]  Dragoljub Kosanovic,et al.  Economic optimization of combined cycle district heating systems , 2014 .

[5]  Antonio Gaspar,et al.  Modelling and Optimisation of , 1999 .

[6]  Erik Dotzauer,et al.  Simple model for prediction of loads in district-heating systems , 2002 .

[7]  Robert Chasnov,et al.  Design and Optimization , 2013 .

[8]  Parham A. Mirzaei,et al.  Urban neighborhood characteristics influence on a building indoor environment , 2015 .

[9]  Giorgia Peri,et al.  On the classification of large residential buildings stocks by sample typologies for energy planning purposes , 2014 .

[10]  Ryohei Yokoyama,et al.  Operational Planning of District Heating and Cooling Systems with Thermal Storage Tanks. , 1995 .

[11]  Antonio L. Avila-Marin,et al.  Evaluation of the potential of central receiver solar power plants: Configuration, optimization and trends , 2013 .

[12]  Giorgia Baccino,et al.  Impact of district heating and groundwater heat pump systems on the primary energy needs in urban areas , 2012 .

[13]  Karen Kensek,et al.  URBAN ENERGY MODELING: GIS AS AN ALTERNATIVE TO BIM , 2014 .

[14]  Jochen Dahm,et al.  District Heating Pipelines in the Ground - Simulation Model - , 2001 .

[15]  A. O. England,et al.  What is Classification , 1946 .

[16]  Kenichi Soga,et al.  GSHP Application for Heating and Cooling at 'City Scale' for the City of Westminster , 2015 .

[17]  Giuliano Dall'O',et al.  A methodology for the energy performance classification of residential building stock on an urban scale , 2012 .

[18]  Toshihiko Nakata,et al.  Optimum design of district heating: Application of a novel methodology for improved design of community scale integrated energy systems , 2012 .

[19]  Harry H. Chenoweth,et al.  Pipe Network Analysis , 1974 .

[20]  Luis M. Serra,et al.  A Simple Method to Calculate Central Solar Heating Plants with Seasonal Storage , 2014 .

[21]  Jianzhong Wu,et al.  Energy consumption and economic analyses of a district heating network , 2013 .

[22]  Kevin Sartor,et al.  Simulation and optimization of a CHP biomass plant and district heating network , 2014 .

[23]  Mauro Reini,et al.  Optimization of a Distributed Cogeneration System with solar district heating , 2014 .

[24]  Jianing Zhao,et al.  A method for the steady-state thermal simulation of district heating systems and model parameters calibration , 2016 .

[25]  David R. Riley,et al.  Using Building Energy Simulation and Geospatial Analysis to Determine Building and Transportation Related Energy Use , 2015 .

[26]  İsmail Yabanova,et al.  Development of ANN model for geothermal district heating system and a novel PID-based control strategy , 2013 .

[27]  Lisa Branchini,et al.  District Heating Network Design and Analysis , 2014 .

[28]  Eui-Jong Kim,et al.  Urban energy simulation: Simplification and reduction of building envelope models , 2014 .

[29]  İsmail Yabanova,et al.  Thermal monitoring and optimization of geothermal district heating systems using artificial neural network: A case study , 2012 .

[30]  Celina Filippín,et al.  Evaluation of heating energy consumption patterns in the residential building sector using stepwise selection and multivariate analysis , 2013 .

[31]  Pingfang Hu,et al.  A Baseline Model for Office Building Energy Consumption in Hot Summer and Cold Winter Region , 2009, 2009 International Conference on Management and Service Science.

[32]  Ursula Eicker,et al.  Simulation and optimization of the district heating network in Scharnhauser Park , 2011 .

[33]  Sven Werner,et al.  Profitability of sparse district heating , 2008 .

[34]  Bernd Möller,et al.  Heat Roadmap Europe: Combining district heating with heat savings to decarbonise the EU energy system , 2014 .

[35]  Markku Lampinen,et al.  Study of a district heating system with the ring network technology and plate heat exchangers in a consumer substation , 2014 .

[36]  Hai Lu,et al.  Energy quality management for building clusters and districts (BCDs) through multi-objective optimization , 2014 .

[37]  Koen Steemers,et al.  Behavioural, physical and socio-economic factors in household cooling energy consumption , 2011 .

[38]  Brian Vad Mathiesen,et al.  4th Generation District Heating (4GDH) Integrating smart thermal grids into future sustainable energy systems , 2014 .

[39]  T. Sowlati,et al.  Economic feasibility of utilizing forest biomass in district energy systems – A review , 2014 .

[40]  Simone Ferrari,et al.  A supporting method for defining energy strategies in the building sector at urban scale , 2013 .

[41]  Dag Henning,et al.  Modelling and optimisation of electricity, steam and district heating production for a local Swedish utility , 2006, Eur. J. Oper. Res..

[42]  Luis M. Serra,et al.  International Conference on Solar Heating and Cooling for Buildings and Industry September 23-25 , 2013 , Freiburg , Germany Comparison of simple methods for the design of central solar heating plants with seasonal storage , 2014 .

[43]  Armin Schnettler,et al.  Multi-objective optimization and simulation model for the design of distributed energy systems , 2016 .

[44]  P. A. Mirzaei,et al.  Recent challenges in modeling of urban heat island , 2015 .

[45]  Jonathan A. Wright,et al.  Optimization of building thermal design and control by multi-criterion genetic algorithm , 2002 .

[46]  Kenichi Soga,et al.  Shallow geothermal energy application with GSHPs at city scale: study on the City of Westminster , 2014 .

[47]  Miao Li,et al.  Economic and environmental optimization for distributed energy resource systems coupled with district energy networks , 2016 .

[48]  Jarmo Söderman,et al.  Optimisation of structure and operation of district cooling networks in urban regions , 2007 .

[49]  Sylvain Serra,et al.  A MINLP optimization of the configuration and the design of a district heating network: Academic study cases , 2016 .

[50]  Niclas Eriksson,et al.  Predicting demand in district heating systems A neural network approach , 2012 .

[51]  Shengwei Wang,et al.  Simplified building model for transient thermal performance estimation using GA-based parameter identification , 2006 .

[52]  Romano Borchiellini,et al.  District heating networks calculation and optimization , 2003 .

[53]  Ursula Eicker,et al.  Impact of load structure variation and solar thermal energy integration on an existing district heating network , 2013 .

[54]  Marc A. Rosen,et al.  District heating and cooling: Review of technology and potential enhancements , 2012 .

[55]  Luis M. Serra,et al.  Evaluation of the Potential of Large Solar Heating Plants in Spain , 2012 .

[56]  XueTao Cheng,et al.  Optimization modeling of district heating networks and calculation by the Newton method , 2013 .

[57]  Carlos E. Pedreira,et al.  Neural networks for short-term load forecasting: a review and evaluation , 2001 .

[58]  Robert L. Johnson,et al.  Finite‐Element Method for Water‐Distribution Networks , 1975 .

[59]  A. Hepbasli.  Thermodynamic analysis of a ground‐source heat pump system for district heating , 2005 .

[60]  Paul A. Fishwick,et al.  Time series forecasting using neural networks vs. Box- Jenkins methodology , 1991, Simul..

[61]  Ignacio E. Grossmann,et al.  Retrospective on optimization , 2004, Comput. Chem. Eng..

[62]  Mauro Reini,et al.  Multicriteria optimization of a distributed energy supply system for an industrial area , 2013 .

[63]  A. Siirde,et al.  OPTIMIZATION OF NARVA DISTRICT HEATING NETWORK AND ANALYSIS OF COMPETITIVENESS OF OIL SHALE CHP BUILDING IN NARVA , 2009 .

[64]  Svend Svendsen,et al.  District heating (DH) network design and operation toward a system-wide methodology for optimizing renewable energy solutions (SMORES) in Canada: A case study , 2012 .

[65]  Masatoshi Sakawa,et al.  Operational planning of district heating and cooling plants through genetic algorithms for mixed 0-1 linear programming , 2002, Eur. J. Oper. Res..

[66]  Daniel E. Fisher,et al.  EnergyPlus: creating a new-generation building energy simulation program , 2001 .

[67]  Agis M. Papadopoulos,et al.  A typological classification of the Greek residential building stock , 2011 .

[68]  Alberto Coronas,et al.  Review of optimization models for the design of polygeneration systems in district heating and cooling networks , 2007 .

[69]  Jeffrey D. Spitler,et al.  Development of the Residential Load Factor Method for Heating and Cooling Load Calculations , 2005 .

[70]  François Maréchal,et al.  Design and optimization of district energy systems , 2007 .

[71]  Nima Amjady,et al.  Short-term hourly load forecasting using time-series modeling with peak load estimation capability , 2001 .

[72]  Thomas Nuytten,et al.  Flexibility of a combined heat and power system with thermal energy storage for district heating , 2013 .

[73]  Juha Jokisalo,et al.  Calculation method and tool for assessing energy consumption in the building stock , 2014 .

[74]  İsmail Yabanova,et al.  Energetic and economic evaluations of geothermal district heating systems by using ANN , 2013 .

[75]  Magnus Åberg,et al.  Optimisation of a Swedish district heating system with reduced heat demand due to energy efficiency measures in residential buildings , 2011 .

[76]  Darko Goricanec,et al.  Optimisation of tree path pipe network with nonlinear optimisation method , 2009 .

[77]  Thomas Kolarik,et al.  Time series forecasting using neural networks , 1994, APL '94.

[78]  Volker Coors,et al.  Citygml-based 3d City Model For Energy Diagnostics And Urban Energy Policy Support , 2013, Building Simulation Conference Proceedings.

[79]  Henrik Madsen,et al.  On flow and supply temperature control in district heating systems , 1994 .

[80]  Michel Noussan,et al.  Biomass-fired CHP and heat storage system simulations in existing district heating systems , 2014 .

[81]  Ursula Eicker,et al.  Control Aspects of Decentralized Solar Thermal Integration into District Heating Networks , 2014 .

[82]  Ming-Wei Chang,et al.  Load forecasting using support vector Machines: a study on EUNITE competition 2001 , 2004, IEEE Transactions on Power Systems.

[83]  Salvatore Carlucci,et al.  Assessing gaps and needs for integrating building performance optimization tools in net zero energy buildings design , 2013 .

[84]  Arif Hepbasli,et al.  A review on energetic, exergetic and exergoeconomic aspects of geothermal district heating systems (GDHSs) , 2010 .

[85]  R. Donachie.  Digital Program for Water Network Analysis , 1974 .

[86]  G. Gross,et al.  Short-term load forecasting , 1987, Proceedings of the IEEE.

[87]  Corneliu T. C. Arsene,et al.  MODELLING AND SIMULATION OF WATER SYSTEMS BASED ON LOOP EQUATIONS , 2004 .

[88]  Markku Lampinen,et al.  Static study of traditional and ring networks and the use of mass flow control in district heating applications , 2013 .

[89]  Andrea Gasparella,et al.  Energy audit of schools by means of cluster analysis , 2015 .

[90]  Y. Shimoda,et al.  Residential end-use energy simulation at city scale , 2004 .

[91]  Michael Y. Hu,et al.  Forecasting with artificial neural networks: The state of the art , 1997 .

[92]  Mohammad S. Al-Homoud,et al.  Computer-aided building energy analysis techniques , 2001 .

[93]  Jørgen Erik Christensen,et al.  Low-energy district heating in energy-efficient building areas , 2011 .

[94]  Arno Schlueter,et al.  Integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts , 2015 .

[95]  Chia-Nan Ko,et al.  Short-term load forecasting using lifting scheme and ARIMA models , 2011, Expert Syst. Appl..

[96]  Christodoulos A. Floudas,et al.  Data-Driven Mathematical Modeling and Global Optimization Framework for Entire Petrochemical Planning Operations , 2016 .